Analytics Engineer

Boston, United StatesOn-site

Responsibilities

Own and deliver end-to-end data pipelines and models that power Sales and Product analytics
Build curated, governed data marts that enable fast, reliable decision-making
Design dimensional data models (dbt) for core entities such as accounts, pipeline, performance, and product usage
Enable reverse ETL workflows to operationalize insights into business systems
Lead and mentor others through design reviews, best practices, and technical guidance
Evolve internal tooling and infrastructure to improve developer and analyst productivity What You’ll Do
Data Quality & Governance: Implement testing frameworks, monitoring, and documentation to ensure trust and compliance

Our Analytics Engineering team sits within a hub-and-spoke model, partnering closely with Go-To-Market (GTM), Product, Engineering, and Business Intelligence teams to build scalable, trusted data systems.
We’re looking for a Senior Analytics Engineer to own end-to-end data pipelines and modeling across GTM (Sales) and Product domains.
Data Modeling & Pipelines: Build and maintain production-grade dbt models in Snowflake
Integrations & Ingestion: Own ingestion from systems like Salesforce, ERP, and product data sources
Repository Stewardship: Maintain dbt codebase, enforce best practices, and ensure scalability
Tooling & Infrastructure: Contribute to Airflow, Terraform, AWS, and other platform tools as needed Who You Are 5+ years of
experience in analytics or data engineering in a modern data stack (Snowflake, BigQuery, or Redshift)
Strong expertise in SQL and dbt, with a focus on building scalable, production-grade data models
Proficiency in Python (or similar) for orchestration or tooling •
Strong communication skills with the ability to partner with non-technical stakeholders •
Experience implementing data testing, monitoring, and governance frameworks
Proven ability to lead cross-functional projects with minimal guidance Nice to Have •
Familiarity with reverse ETL tools and workflows •
Experience with Airflow, Fivetran, Workato, or similar tools AWS
experience (S3, EC2, Lambda) and infrastructure-as-code (Terraform)

You’ll help build the foundation that powers everything from forecasting and compensation to product insights and experimentation.
Experience with Sales Operations, compensation, or GTM analytics
Our salary range reflects the cost of labor across various U.S. geographic markets.
The range displayed below reflects the minimum and maximum target salaries for the position across all our US locations.
The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location.
In addition to base salary, our total compensation package may include participation in the company’s annual cash bonus plan, variable compensation (OTE) for sales and customer success roles, equity, sign-on payments, and a comprehensive range of health, welfare, and wellbeing
Your recruiter can provide more details about the specific salary/OTE range for your preferred location during the hiring process.
Base Pay Range For US Locations: $112,000 — $168,000 USD

Want to learn more about life at Klaviyo? Visit klaviyo.com/careers to see how we empower creators to own their own destiny. About the Team

At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day.
We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements.
If you’re a close but not exact match with the description, we hope you’ll still consider applying.
Data is at the heart of every decision at Klaviyo.
You’ll work at the intersection of business and engineering, owning core data models, enabling self-service analytics, and ensuring our data ecosystem is reliable, scalable, and compliant. About the Role
You’ll build and maintain the source of truth for operational and product data, enabling leadership, analysts, and product teams to answer complex questions with confidence.
This role combines deep technical execution with high-impact business partnership, requiring you to translate ambiguous needs into scalable data products.
You will operate as a trusted, embedded partner to stakeholders while leveraging the broader Data Engineering organization’s standards, tooling, and best practices.
Partner with Sales, Product, and Analytics teams to create holistic views of the customer and product lifecycle
Raise the bar on data quality, testing, monitoring, and documentation